Location: CET or EST time zone
*We are not actively seeking a Data Scientist at the moment. BUT you are encouraged to send your resume so when we are ready to hire, we may contact you.
Who is FNA?
FNA is a fast growing, deep technology company rooted in finance. Our flagship product, the FNA Platform allows financial institutions to map and monitor complex financial networks and to simulate operational and financial risks. Over a decade of pioneering research into financial graph analytics makes the company a leader in its field. FNA’s clients include the world’s largest central banks, financial market infrastructures and financial institutions. FNA’s mission is to bring graph analytics to the financial services mainstream and to play a pivotal role in the growing graph analytics ecosystem, where FNA’s engine powers use cases across a growing number of business domains.
Who are we looking for?
Bright, forward-thinking and motivated professionals who want to be challenged and rewarded accordingly. If you enjoy finding creative solutions to tough problems, this is your chance to take an active role and leave your mark. Use your curiosity and apply our advanced software to change the way analytics and machine learning is being applied in finance and make our financial systems safer.
What are the benefits of Joining FNA?
- FNA’s mission is to make our global financial systems safer and more efficient
- Opportunity to expand your career with additional duties and job titles as the company grows
- High-growth start-up working on the development of exciting next generation, machine learning, and Big-Data analytics solutions
- Be part of a team of collaborative, brilliant, passionate, hard-working & humble colleagues who embrace working from anywhere there is a solid internet connection
- Entrepreneurial spirit at every level of the company
- FNA fully supports, encourages and assists in your personal and professional growth
- Participation in the FNA yearly Network Science conferences in London
Key Areas of Responsibilities:
- Using the FNA platform and scripting language, the data scientist will be responsible to identify hidden behavioural patterns and interconnections in large datasets, helping to create breakthrough solutions, performing exploratory and targeted data analyses as part of quantitative services engagements or proof of concepts
- With time, the Data Scientist will be customer facing to develop and present customer specific use cases clearly and concisely, communicate analyses, recommendations, status and results to existing customers and prospects at business management and executive level
- You will be heavily involved in the research and development of new use-cases, either as part of our product road-map or based on specific customer requirements
- With time, deliver customer-facing workshops
- The right candidates will have experience and knowledge of Machine Learning concepts and will be allowed freedom to explore new concepts to help develop future products
- Partner with cross-functional teams to solve business problems at scale and identify trends/opportunities for the customers
- Customer Excellence – Effectively help to resolve relevant customer support requests in a professional and timely manner
- Strong written documentation skills to facilitate our blog/articles/use-cases/releases etc.
- 2+ years experience with machine learning and predictive modelling within large datasets
- 2+ years commercial experience as a Data Scientist
- You will have excellent analytical and problem solving skills using a range of data analysis or statistical techniques
- Recent graduate (MSc or higher) in Big Data, Machine Learning, Statistics, Mathematics, or another similar field
- Business level written and spoken English is a minimum
- The right candidate will be naturally inquisitive, analytical and have good attention to detail. You should have the ability to communicate technical findings to non-technical personnel and not be afraid to present creative, data-driven ideas to your colleagues
- Applying abstract mathematical concepts to noisy, real-world data
Nice To Haves
- PhD level qualification in mathematics, statistics, physics, engineering or similar
- Familiarity with network science/graph analytics
- 3rd and 4th Business Level Language very beneficial